Legal AI for enterprise commercial teams
Run contracts like a large enterprise without the legal overhead
Ask Genie to draft a customer agreement for our mid-market workflow...
Ask Genie to draft a customer agreement for our mid-market workflow...
Ask Genie to review this counterparty MSA against our mid-market playbook...
Ask Genie to find the right template for our mid-market workflow...
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What GenieAI is and how it handles your contract process
GenieAI is an AI legal agent used by 200,000+ business teams to create, review, and negotiate contracts without an in-house lawyer. It drafts customer, vendor, employment, and partnership agreements with current-law accuracy across 150+ jurisdictions, flags risk red, amber, or green against your own playbook, and returns track-changed redlines ready to sign.
The platform pairs specialist legal technology with a consistency layer, so risk stays controlled on every deal and your commercial team can move fast with confidence. GenieAI is 140% more accurate than ChatGPT (see plans and pricing), and customers report closing deals 70% faster once contracting stops being the bottleneck. The system is built on legal research and models trained to understand clause language in context, so it answers questions about your terms and generates drafts you can rely on. Data is handled under ISO 27001 information security, with a published privacy policy governing how your documents are stored and used.
Support runs the whole way through, from setting the rules once to getting help on a specific clause, so legal work gets done in the time a deal actually allows. Different teams, from sales to operations, get the same access to a shared playbook, giving every user the insight to sign with confidence. Start with a free non-disclosure agreement or move straight to your commercial contracts.
- Create and manage customer, vendor, and employment agreements at scale
- Standardise playbook across functions before legal becomes the bottleneck
- 500+ scale-up-ready templates across 150+ jurisdictions, free to use
What you can do
Use cases for Mid-Market
Each of these is a workflow Genie handles end-to-end. Click any use case to see how it works.
How we compare
How does GenieAI compare to ChatGPT?
Other company types
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Common questions
Mid-Market FAQs
Legal has become the bottleneck as we grow. What is the fix?
Usually not more headcount. Most of the queue is the same incoming terms being reviewed repeatedly, so settling those positions once as a playbook and reviewing against it removes the wait without giving up control.
The risk of a bottleneck is not delay on its own. It is that commercial teams start signing without review because waiting costs them the deal.
How do we set contract standards the commercial team will actually follow?
Write them as positions rather than policy: what we accept, what we can concede, and what has to escalate. Anything outside the agreed positions is flagged rather than silently approved.
Standards fail when they live in a document nobody opens. They work when they are applied to the contract in front of the person doing the deal.
What contract risks do scaling businesses miss most often?
Uncapped liability and broad indemnities on customer paper, auto-renewal and price escalation in supplier terms, missing data processing agreements, and IP assignments that were never signed by contractors.
Each looks minor in isolation, which is why they are missed. They matter at diligence, where they are repriced rather than negotiated.
How do we move from ad hoc contracts to a repeatable process?
Start with the documents you sign most often, agree the standard positions for them, and put those into a playbook. Master service agreements, NDAs and supplier agreements usually account for most of the volume.
Working in that order matters. Standardising the long tail first produces a lot of documentation and very little reduction in risk.
Do we need a contract management system as well?
Not necessarily at this stage. Storage and reporting help once the volume is large, but for most scaling businesses the exposure is in what the contracts say rather than in finding them again afterwards.
It is worth being clear which problem you are solving. Consistent drafting and review addresses risk; a repository addresses retrieval.
Is GenieAI right for a mid-market legal team?
Yes. GenieAI scales from teams of 2 to teams of 200 with the same product - pricing scales linearly, no enterprise tier required for core features.
How fast can a mid-market team onboard?
Most mid-market teams are productive within a week. Playbook ingestion, integration setup, and team training are bundled into onboarding - no professional-services engagement required.
What ROI do mid-market customers see?
Mid-market customers typically report 60-80% reduction in contract review cycle time, with proportional reductions in external-counsel spend. Most reach payback within 3-6 months.
Trusted by 200,000+ users
Drafts, reviews, and negotiates contracts autonomously.
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